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Radiation Protection & Shielding
The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
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2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Oak Ridge community roundtable explores workforce challenges
Federal and contractor officials, community leaders, and educators gathered in Knoxville, Tenn., on October 29 for a roundtable event focused on ensuring the Oak Ridge Office of Environmental Management (OREM) and its partners have the resources and infrastructure needed to support a robust, talented workforce in the years ahead.
Kaushik Banerjee, William R. Martin
Nuclear Science and Engineering | Volume 174 | Number 1 | May 2013 | Pages 30-45
Technical Paper | doi.org/10.13182/NSE11-94
Articles are hosted by Taylor and Francis Online.
Monte Carlo point detector and surface crossing flux tallies are two widely used tallies, but they suffer from an unbounded variance. As a result, the central limit theorem cannot be used for these tallies to estimate confidence intervals. By construction, kernel density estimator (KDE) tallies can be directly used to estimate flux at a point, but the variance of this point estimate does not converge as 1/N, which is not unexpected for a point quantity. However, an improved approach is to modify both point detector and surface crossing flux tallies directly by using KDE within a variance reduction approach and taking advantage of the fact that KDE estimates the underlying probability density function. This methodology is illustrated by several numerical examples and shows numerically that both the surface crossing tally and the point detector tally converge as 1/N (in variance), and both are asymptotically unbiased.